The Lobo Lab

Systems Biology of Growth & Form

At the Lobo Lab we reverse engineer the mechanisms regulating biological growth and form with an integrated systems approach. We focus on understanding, controlling, and designing the dynamic regulation and signaling that control how organisms grow, metabolize their components, and coordinate the formation of patterns and shapes. We closely integrate new computational methods, mathematical models, and bioinformatics approaches with molecular assays at the bench. We seek a mechanistic understanding of development and regeneration, find therapies for cancer and other diseases, and streamline the application of systems and synthetic biology.

News

- A new NIH-funded Postdoctoral Research Associate position in Computational Biology is currently available to join the lab. Apply here!

- Archana receives an Academic Fellowship from Merck. Congratulations Archana!

- Daniel is promoted to Associate Professor and granted Tenure. Congratulations to the whole lab!.

- Daniel gives a talk at the UC Riverside Interdisciplinary Center for Quantitative Modeling in Biology.


Planarian worms simulation

Systems Biology

We build quantitative mathematical models to understand, analyze, and predict the behavior of biological systems.

Computational AI methods

Computational Methods

We develop computational methods to simulate and infer dynamic models, discover novel elements, and find the best next experiments to test.

Planform

Ontologies and Databases

We create ontologies, curate databases, and develop expert systems used by both human scientists and artificial intelligence machines.

Planarian regeneration

Development and Regeneration

We study how shapes and patterns are formed from a single cell during development and restored through regeneration.

Cancer phenotypes

Cancer and other Diseases

We seek to understand why and how regulatory mechanisms go awry to produce cancer and other diseases.

Knockout metabolic network

Synthetic Biology

We design and optimize regulatory and metabolic networks with desired dynamics and behaviors to solve specific bioengineering problems.